In this paper, we study finite-time control of multiagent networks as systems, where they involve floating agents that exchange local information and driver agents that not only exchange local information but also take input and output roles. For this class of multiagent networks, control algorithms are applied to the driver agents based on the measurements collected from them for the purpose of influencing the overall behavior of the resulting system. Specifically, we consider time-critical applications in the control of multiagent networks as systems and propose a finite-time control approach predicated on a recent time transformation method. The proposed method guarantees execution of control algorithms over a prescribed time interval $[0,T)$ with $T$ being a user-defined convergence time based on analysis performed over a stretched, infinite-time interval $[0,\infty )$. We analytically show that the resulting system achieves user-defined finite-time convergence regardless of the initial conditions of agents, where we also discuss the separation principle obtained with the proposed method. The presented theoretical contributions are not only illustrated by numerical examples but also experimentally validated using ground mobile robots.

在本文中，我们研究了作为系统的多主体网络的有限时间控制，其中它们涉及交换本地信息的浮动代理和不仅交换本地信息而且还承担输入和输出角色的驱动程序代理。对于此类多代理程序网络，基于从驱动程序代理收集的测量值，将控制算法应用于驱动程序代理，以影响所得系统的整体行为。具体来说，我们将对时间至关重要的应用程序作为系统在多智能体网络的控制中的应用，并提出一种基于最近时间转换的有限时间控制方法方法。所提出的方法保证在规定的时间间隔内执行控制算法$[0，Ť）$ 与 $Ť$ 是用户定义的收敛时间，基于在无限长的时间间隔内执行的分析 $[0，\infty ）$。我们通过分析表明，无论代理的初始条件如何，生成的系统都可以实现用户定义的有限时间收敛，在此我们还讨论了使用所提出的方法获得的分离原理。提出的理论贡献不仅通过数值示例进行了说明，而且使用地面移动机器人进行了实验验证。